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For model-assisted estimation, the variance estimator of the so-called generalized regression estimator is [60].

The superpopulation variance estimator provided better estimates than the robust sandwich variance estimator and the WC model provided accurate estimates of the effects of correlated aspects of temporal patterns of exposure.

Regarding variance estimation, Osier (2006, 2009) proposed a variance estimator based on linearization techniques.

Standard errors were estimated using the robust variance estimator (Barlow 1994; Barlow et al. 1999).

As suggested by the ratio ASE/SDE, the superpopulation variance estimator (WC2) tended to give estimates that were closer to the true variance than the robust variance estimator (WC1) that systematically under-estimated the true variance.

Standard errors were estimated using the robust variance estimator proposed by Barlow (Barlow 1994; Barlow et al. 1999).

A variance estimator based on Schoenfeld residuals provided better variance estimates for severe model misspecification [ 32].

A variance estimator is obtained by inserting the estimated covariance matrix in Eq. (7).

Accounting for uncertainty in the weight estimates could further improve the variance estimator [ 31].

The interpolated variance estimator (IVE) is a new method which can estimate the uncertainty based on direct discharge measurements.

We also propose a variance estimator of the SMPL estimator.

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